Dynamic License Plate Localization for Vehicles on Multi-lane Using Single Camera

Hung Li Tseng; Chao Nan Hung; Chiu Ching Tuan; You Ru Wen; Wen Tzeng Huang; Chin Hsing Chen

doi:10.4028/www.scientific.net/AMM.300-301.740

Paper Titles

A Robust P300-Speller Brain-Computer Interface Based on Kernel PCA
p.721

A Novel Improved Algorithm of Radial Feature Code Extraction
p.725

Embedded Machine Vision System Design Based on Davinci DM355
p.729

A Novel Fuzzy Clustering Method with No Outliers Influence
p.735

Dynamic License Plate Localization for Vehicles on Multi-lane Using Single Camera
p.740

Application of Weighted Projection PM Algorithm in Estimation of DOA
p.746

Research on Wavelet Compression and Reconstruction of Wind Turbine Vibration Signal
p.753

System-Reliability Evaluation Based on Series Chain Model under Exponential Distribution
p.758

A New Method for the Eigenvalue Problem of Structures with Uncertain-but-Non-Random Parameters
p.765

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 300-301Dynamic License Plate Localization for Vehicles on...

Dynamic License Plate Localization for Vehicles on Multi-lane Using Single Camera

Abstract:

LPR (License Plate Recognition) System has been widely used in highway toll collection, parking management, various traffic regulations enforcement and other systems. Currently, most of the existing LPL (license plate localization) systems are with single camera that is limited to recognizing vehicles in one lane. In this paper we design a license plate localization system that simultaneously recognizes license plates of vehicles on multi-lane by using single high-resolution camera. Our approach significantly reduces the hardware cost of LPR system without sacrificing the accuracy of recognition. And our success rate is about 94%.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 300-301)

Pages:

740-745

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.300-301.740

Citation:

Cite this paper

Online since:

February 2013

Authors:

Hung Li Tseng, Chao Nan Hung, Chiu Ching Tuan, You Ru Wen, Wen Tzeng Huang, Chin Hsing Chen

Keywords:

Edge Detection, License Plate Recognition, Multiple-Lane

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] S.L. Chang, L. S. Chen, Y. C. Chung and S. W. Chen: Automatic license plate recognition, IEEE Transactions on Intelligent Transportation Systems, Vol. 5, (2004), pp.42-53.

DOI: 10.1109/tits.2004.825086

Google Scholar

[2] C.T. Hsieh, Y.S. Juan and K. M. Hung: Multiple License Plate Detection for Complex Background, 19th Int. Advanced Information Networking and Applications, IEEE (2005).

DOI: 10.1109/aina.2005.257

Google Scholar

[3] R.C. Gonzalez and R.E. Woods: Digital Image Processing, Addison-Wesley (1992).

Google Scholar

[4] M. Sonka, V. Hilavac and R. Boyle: Image Processing Analysis, and Machine Vision, PWS Publishing (1998).

Google Scholar

[5] Y.K. Kim, J.K. Paik and B.S. Kang: Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering, IEEE Trans. Consumer Electronics, Vol. 44, No. (1998), pp.82-86.

DOI: 10.1109/30.663733

Google Scholar

[6] R.C. Gonzalez and W.R. Richard: Digital Image Processing (Second Edition), Prentice Hall, international edition, (2002), pp.136-138.

Google Scholar

[7] N. Otsu: A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, (1979), pp.62-66.

DOI: 10.1109/tsmc.1979.4310076

Google Scholar

[8] J.W. Hsieh, S.H. Yu and Y.S. Chen: Morphology-based　License Plate Detection from Complex Scenes, Yuan Ze University, Department of Electrical Engineering, (2002).

Google Scholar

[9] D.S. Gao and J. Zhou: Car License Plates Detection from Complex Scene, Tsinghua University, Department of　Automation, P.R. China, (2000).

Google Scholar

[10] Yanamura. Y, et al, Extraction and Tracking of the License Plate using Hough Transform and Voted Block Matching, Proceedings of IEEE Intelligent Vehicles Symposium, (2003), pp.243-246.

DOI: 10.1109/ivs.2003.1212916

Google Scholar